A central role in understanding the interaction between humans and AI plays the notion of trust. Especially research from social and cognitive psychology has shown, however, that individuals’ perceptions of trust can be biased. In this empirical investigation, we focus on the single and combined effects of attitudes towards AI and motivated reasoning in shaping such biased trust perceptions in the context of news consumption. In doing so, we rely on insights from works on the machine heuristic and motivated reasoning. In a 2 (author) x 2 (congruency) between-subjects online experiment, we asked N = 477 participants to read a news article purportedly written either by AI or a human author. We manipulated whether the article represented pro or contra arguments of a polarizing topic, to elicit motivated reasoning. We also assessed participants’ attitudes towards AI in terms of competence and objectivity. Through multiple linear regressions, we found that (a) increased perceptions of AI as objective and ideologically unbiased increased trust perceptions, whereas (b), in cases where participants were swayed by their prior opinion to trust content more when they agreed with the content, the AI author reduced such biased perceptions. Our results indicate that it is crucial to account for attitudes towards AI and motivated reasoning to accurately represent trust perceptions.
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